code stringlengths 81 54k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
import time
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch, torch_device
from ..test_modeling_common import ids_tensor
if is_torch_available():
import torch
from transformers.generation import (
... | 709 |
"""simple docstring"""
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_multi_gpu
from accelerate.utils import patch_environment
class __UpperCamelCas... | 16 | 0 |
import json
import multiprocessing
import os
import re
from collections import defaultdict
import torch
from accelerate import Accelerator
from accelerate.utils import set_seed
from arguments import HumanEvalArguments
from datasets import load_dataset, load_metric
from torch.utils.data import IterableDa... | 710 |
"""simple docstring"""
from __future__ import annotations
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstring'''
create_state_space_tree(_lowerCamelCase , [] , 0 , [0 for i in range(len(_lowerCamelCase ) )] )
def lowerCamelCase__ ( _lowerCam... | 16 | 0 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class __UpperCamelCase ( metaclass=a__ ):
_UpperCAmelCase = ["sentencepiece"]
def __init__( self ,*_A ,**_A ):
'''simple docstring'''
requires_backends(self ,['sentencepiece'] ... | 711 |
"""simple docstring"""
import logging
import os
from .state import PartialState
class __UpperCamelCase ( logging.LoggerAdapter ):
@staticmethod
def __lowerCamelCase ( _A ):
'''simple docstring'''
_lowerCAmelCase : Optional[Any] = ... | 16 | 0 |
import contextlib
import importlib
import io
import unittest
import transformers
# Try to import everything from transformers to ensure every object can be loaded.
from transformers import * # noqa F406
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, require_tf, require_to... | 712 |
"""simple docstring"""
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert import BertTokenizer
_lowerCAmelCase =... | 16 | 0 |
"""simple docstring"""
def lowerCamelCase__ ( _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
if len(_lowerCamelCase ) != len(_lowerCamelCase ):
raise ValueError('String lengths must match!' )
_lowerCAmelCase : int = 0
fo... | 713 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, skip_... | 16 | 0 |
"""simple docstring"""
import importlib
import shutil
import threading
import warnings
from typing import List
import fsspec
import fsspec.asyn
from . import compression
from .hffilesystem import HfFileSystem
_lowerCAmelCase = importlib.util.find_spec("""s3fs""") is not None
i... | 714 |
"""simple docstring"""
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class __UpperCamelCase... | 16 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowerCAmelCase = {
"""configuration_blenderbot_small""": [
... | 715 |
"""simple docstring"""
import argparse
import json
import os
from pathlib import Path
import requests
import torch
from transformers import JukeboxConfig, JukeboxModel
from transformers.utils import logging
logging.set_verbosity_info()
_lowerCAmelCase = logging.get_logger(__name_... | 16 | 0 |
"""simple docstring"""
import os
def lowerCamelCase__ ( ):
'''simple docstring'''
_lowerCAmelCase : List[Any] = os.path.join(os.path.dirname(_lowerCamelCase ) , 'num.txt' )
with open(_lowerCamelCase ) as file_hand:
return str(sum(int(_lowerCamelCase ... | 716 |
"""simple docstring"""
from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
_lowerCAmelCase = {"""UserAgent""": UserAgent().random}
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstr... | 16 | 0 |
"""simple docstring"""
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : List[str] = 1
for i in range(1 , num + 1 ):
fact *= i
return fact
def lowerCamelCase__ ( _lowerCamelCase ):
'''simpl... | 717 |
"""simple docstring"""
import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import SPIECE_UNDERLINE, logging
_lowerCAmelCase... | 16 | 0 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging
_lowerCAmelCase = logging.get_lo... | 718 |
"""simple docstring"""
import argparse
import struct
import unittest
class __UpperCamelCase :
def __init__( self ,_A ):
'''simple docstring'''
_lowerCAmelCase : Optional[int] = data
# Initialize hash values
_lowerCAmelCase ... | 16 | 0 |
"""simple docstring"""
import logging
import os
from typing import List, TextIO, Union
from conllu import parse_incr
from utils_ner import InputExample, Split, TokenClassificationTask
_lowerCAmelCase = logging.getLogger(__name__)
class __UpperCamelCase ( a__ ... | 719 |
"""simple docstring"""
from collections.abc import Callable
class __UpperCamelCase :
def __init__( self ,_A = None ):
'''simple docstring'''
_lowerCAmelCase : list = []
# Stores indexes of each item for supporting updates and deletion.... | 16 | 0 |
"""simple docstring"""
from math import factorial
def lowerCamelCase__ ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
if successes > trials:
raise ValueError('successes must be lower or equal to trials' )
if trials < 0 o... | 720 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Dict, Optional, Union
import torch
import torch.nn.functional as F
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTra... | 16 | 0 |
"""simple docstring"""
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
FEATURE_EXTRACTOR_MAPPING,
AutoConfig,
AutoFeatureExtractor,
WavaVecaConfig,
WavaVecaFeatureExtract... | 721 |
"""simple docstring"""
# Lint as: python3
import sys
from collections.abc import Mapping
from typing import TYPE_CHECKING, Dict, Optional
import numpy as np
import pyarrow as pa
from .. import config
from ..utils.logging import get_logger
from ..utils.py_utils import map_nested
from .forma... | 16 | 0 |
"""simple docstring"""
import random
import unittest
import numpy as np
import transformers
from transformers import is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax
if is_flax_available():
import os
import jax.numpy as... | 700 |
"""simple docstring"""
from math import acos, sin
from typing import List, Tuple, Union
import numpy as np
import torch
from PIL import Image
from ...models import AutoencoderKL, UNetaDConditionModel
from ...schedulers import DDIMScheduler, DDPMScheduler
from ...utils import randn_tensor
fr... | 16 | 0 |
"""simple docstring"""
import argparse
import re
import numpy as np
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SamConfig,
SamImageProcessor,
SamModel,
SamProcessor,
SamVisionConfig,
)
... | 701 |
"""simple docstring"""
import json
import os
from typing import Dict, List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_lowerCAmelCase = logging.get_logger(__name__)
_lowerCAmelCase = {
"""vocab_file""": """vocab.j... | 16 | 0 |
import json
import os
from functools import lru_cache
from typing import TYPE_CHECKING, List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import Convers... | 702 |
"""simple docstring"""
import math
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from .attention_processor import Attention
from .embeddings import get_timestep_embedding
from .modeling_utils import ModelMixin
class __Upper... | 16 | 0 |
"""simple docstring"""
import inspect
import jax
import jax.lax as lax
import jax.numpy as jnp
from ..utils import add_start_docstrings
from ..utils.logging import get_logger
_lowerCAmelCase = get_logger(__name__)
_lowerCAmelCase = r"""
Args:
input_ids (`jnp.n... | 703 |
"""simple docstring"""
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import ResNetConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_visio... | 16 | 0 |
import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import PaddingStrategy, logging... | 704 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Callable
_lowerCAmelCase = list[list[float | int]]
def lowerCamelCase__ ( _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : int = len... | 16 | 0 |
"""simple docstring"""
import argparse
import struct
import unittest
class __UpperCamelCase :
def __init__( self ,_A ):
'''simple docstring'''
_lowerCAmelCase : Optional[int] = data
# Initialize hash values
_lowerCAmelCase ... | 705 |
"""simple docstring"""
import argparse
import json
from typing import List
from ltp import LTP
from transformers import BertTokenizer
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstring'''
if (
(cp >= 0X4E00 and cp <= 0X9FFF)
or (cp >= 0... | 16 | 0 |
"""simple docstring"""
from ..models.auto import AutoModelForSeqaSeqLM, AutoTokenizer
from .base import PipelineTool
_lowerCAmelCase = {
"""Acehnese Arabic""": """ace_Arab""",
"""Acehnese Latin""": """ace_Latn""",
"""Mesopotamian Arabic""": """acm_Arab""",
"""Ta'izzi-Ade... | 706 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LDMTextToImagePipeline, UNetaDConditionModel
from diffusers.utils.testing_utils import (
... | 16 | 0 |
"""simple docstring"""
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except Optio... | 707 |
"""simple docstring"""
import baseaa
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstring'''
return baseaa.aaaencode(string.encode('utf-8' ) )
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstring'''
return baseaa.aaadecod... | 16 | 0 |
"""simple docstring"""
import json
import os
import unittest
from transformers import DebertaTokenizer, DebertaTokenizerFast
from transformers.models.deberta.tokenization_deberta import VOCAB_FILES_NAMES
from transformers.testing_utils import slow
from ...test_tokenization_common import Token... | 708 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bert import BertTokenizer
_lowerCAmelCase = logging.get_logge... | 16 | 0 |
"""simple docstring"""
import argparse
import json
from typing import List
from ltp import LTP
from transformers import BertTokenizer
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstring'''
if (
(cp >= 0X4E00 and cp <= 0X9FFF)
or (cp >= 0... | 709 |
"""simple docstring"""
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_multi_gpu
from accelerate.utils import patch_environment
class __UpperCamelCas... | 16 | 0 |
from pathlib import Path
from typing import List
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import get_tests_dir, is_tool_test
from transformers.tools.agent_types import AGENT_TYPE_MAPPING, AgentAudio, AgentImage, AgentText
if is_torch_available():
... | 710 |
"""simple docstring"""
from __future__ import annotations
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstring'''
create_state_space_tree(_lowerCamelCase , [] , 0 , [0 for i in range(len(_lowerCamelCase ) )] )
def lowerCamelCase__ ( _lowerCam... | 16 | 0 |
"""simple docstring"""
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstring'''
if not isinstance(_lowerCamelCase , _lowerCamelCase ):
_lowerCAmelCase : List[str] = f"""Input value of [number={number}] must be an integer"""
raise TypeError(_lowerCamel... | 711 |
"""simple docstring"""
import logging
import os
from .state import PartialState
class __UpperCamelCase ( logging.LoggerAdapter ):
@staticmethod
def __lowerCamelCase ( _A ):
'''simple docstring'''
_lowerCAmelCase : Optional[Any] = ... | 16 | 0 |
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_multi_gpu
from accelerate.utils import patch_environment
class __UpperCamelCase ( unittest.TestCase ):
... | 712 |
"""simple docstring"""
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert import BertTokenizer
_lowerCAmelCase =... | 16 | 0 |
"""simple docstring"""
from ....configuration_utils import PretrainedConfig
from ....utils import logging
_lowerCAmelCase = logging.get_logger(__name__)
_lowerCAmelCase = {
"""speechbrain/m-ctc-t-large""": """https://huggingface.co/speechbrain/m-ctc-t-large/resolve/main/config... | 713 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, skip_... | 16 | 0 |
"""simple docstring"""
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalyt... | 714 |
"""simple docstring"""
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class __UpperCamelCase... | 16 | 0 |
"""simple docstring"""
import collections.abc
from typing import Optional, Tuple, Union
import torch
import torch.utils.checkpoint
from torch import nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import BaseModelOutputWithNoAtten... | 715 |
"""simple docstring"""
import argparse
import json
import os
from pathlib import Path
import requests
import torch
from transformers import JukeboxConfig, JukeboxModel
from transformers.utils import logging
logging.set_verbosity_info()
_lowerCAmelCase = logging.get_logger(__name_... | 16 | 0 |
"""simple docstring"""
import json
import os
from typing import Dict, List, Optional, Tuple
import regex as re
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_lowerCAmelCase = logging.get_logger(__name__)
_lowerCAmelCase = {
"""voc... | 716 |
"""simple docstring"""
from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
_lowerCAmelCase = {"""UserAgent""": UserAgent().random}
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstr... | 16 | 0 |
"""simple docstring"""
import logging
import os
from .state import PartialState
class __UpperCamelCase ( logging.LoggerAdapter ):
@staticmethod
def __lowerCamelCase ( _A ):
'''simple docstring'''
_lowerCAmelCase : Optional[Any] = ... | 717 |
"""simple docstring"""
import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import SPIECE_UNDERLINE, logging
_lowerCAmelCase... | 16 | 0 |
"""simple docstring"""
import unittest
from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script
@require_cpu
class __UpperCamelCase ( unittest.TestCase ):
def __lowerCamelCase ( self ):
'''simple docstr... | 718 |
"""simple docstring"""
import argparse
import struct
import unittest
class __UpperCamelCase :
def __init__( self ,_A ):
'''simple docstring'''
_lowerCAmelCase : Optional[int] = data
# Initialize hash values
_lowerCAmelCase ... | 16 | 0 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import AutoencoderKL, DDIMScheduler, DiTPipeline, DPMSolverMultistepScheduler, TransformeraDModel
from diffusers.utils import is_xformers_available, load_numpy, slow, torch_device
from diffusers.ut... | 719 |
"""simple docstring"""
from collections.abc import Callable
class __UpperCamelCase :
def __init__( self ,_A = None ):
'''simple docstring'''
_lowerCAmelCase : list = []
# Stores indexes of each item for supporting updates and deletion.... | 16 | 0 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
from transformers import BatchEncoding, CanineTokenizer
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.tokenization_utils import AddedToken
from transformers.... | 720 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Dict, Optional, Union
import torch
import torch.nn.functional as F
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTra... | 16 | 0 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import center_crop, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils... | 721 |
"""simple docstring"""
# Lint as: python3
import sys
from collections.abc import Mapping
from typing import TYPE_CHECKING, Dict, Optional
import numpy as np
import pyarrow as pa
from .. import config
from ..utils.logging import get_logger
from ..utils.py_utils import map_nested
from .forma... | 16 | 0 |
"""simple docstring"""
import argparse
import torch
from transformers import BertConfig, BertForPreTraining, load_tf_weights_in_bert
from transformers.utils import logging
logging.set_verbosity_info()
def lowerCamelCase__ ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase ... | 700 |
"""simple docstring"""
from math import acos, sin
from typing import List, Tuple, Union
import numpy as np
import torch
from PIL import Image
from ...models import AutoencoderKL, UNetaDConditionModel
from ...schedulers import DDIMScheduler, DDPMScheduler
from ...utils import randn_tensor
fr... | 16 | 0 |
"""simple docstring"""
from __future__ import annotations
from math import pi
# Define the Reduced Planck Constant ℏ (H bar), speed of light C, value of
# Pi and the function
_lowerCAmelCase = 1.054_571_817E-34 # unit of ℏ : J * s
_lowerCAmelCase = 3E8 # unit of c : m * s^-1
... | 701 |
"""simple docstring"""
import json
import os
from typing import Dict, List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_lowerCAmelCase = logging.get_logger(__name__)
_lowerCAmelCase = {
"""vocab_file""": """vocab.j... | 16 | 0 |
import copy
import unittest
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_mo... | 702 |
"""simple docstring"""
import math
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from .attention_processor import Attention
from .embeddings import get_timestep_embedding
from .modeling_utils import ModelMixin
class __Upper... | 16 | 0 |
"""simple docstring"""
from __future__ import annotations
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstring'''
return [ord(_lowerCamelCase ) - 96 for elem in plain]
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstring'''
... | 703 |
"""simple docstring"""
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import ResNetConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_visio... | 16 | 0 |
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstring'''
if not isinstance(_lowerCamelCase , _lowerCamelCase ):
raise ValueError('Input must be an integer' )
if input_num <= 0:
raise ValueError('Input must be positive' )
return sum(
div... | 704 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Callable
_lowerCAmelCase = list[list[float | int]]
def lowerCamelCase__ ( _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : int = len... | 16 | 0 |
"""simple docstring"""
import argparse
import datetime
import json
import time
import warnings
from logging import getLogger
from pathlib import Path
from typing import Dict, List
import torch
from tqdm import tqdm
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from utils ... | 705 |
"""simple docstring"""
import argparse
import json
from typing import List
from ltp import LTP
from transformers import BertTokenizer
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstring'''
if (
(cp >= 0X4E00 and cp <= 0X9FFF)
or (cp >= 0... | 16 | 0 |
"""simple docstring"""
import json
import os
import unittest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTeste... | 706 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LDMTextToImagePipeline, UNetaDConditionModel
from diffusers.utils.testing_utils import (
... | 16 | 0 |
"""simple docstring"""
_lowerCAmelCase = {str(digit): digit**5 for digit in range(1_0)}
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstring'''
return sum(DIGITS_FIFTH_POWER[digit] for digit in str(_lowerCamelCase ) )
def lowerCamelCase__ ( ):
... | 707 |
"""simple docstring"""
import baseaa
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstring'''
return baseaa.aaaencode(string.encode('utf-8' ) )
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstring'''
return baseaa.aaadecod... | 16 | 0 |
"""simple docstring"""
from __future__ import annotations
from decimal import Decimal
from numpy import array
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : Any = Decimal
# Check if the provided matrix has 2 rows... | 708 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bert import BertTokenizer
_lowerCAmelCase = logging.get_logge... | 16 | 0 |
"""simple docstring"""
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
if is_torch_available():
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
... | 709 |
"""simple docstring"""
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_multi_gpu
from accelerate.utils import patch_environment
class __UpperCamelCas... | 16 | 0 |
import collections
import json
import os
import re
from typing import TYPE_CHECKING, List, Optional, Tuple
import numpy as np
from ...tokenization_utils_fast import PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import Conversation
... | 710 |
"""simple docstring"""
from __future__ import annotations
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstring'''
create_state_space_tree(_lowerCamelCase , [] , 0 , [0 for i in range(len(_lowerCamelCase ) )] )
def lowerCamelCase__ ( _lowerCam... | 16 | 0 |
"""simple docstring"""
import argparse
from pathlib import Path
import torch
from transformers import OPTConfig, OPTModel
from transformers.utils import logging
logging.set_verbosity_info()
_lowerCAmelCase = logging.get_logger(__name__)
def lowerCamelCase__ ( _lowerCamelCase ):
'''simpl... | 711 |
"""simple docstring"""
import logging
import os
from .state import PartialState
class __UpperCamelCase ( logging.LoggerAdapter ):
@staticmethod
def __lowerCamelCase ( _A ):
'''simple docstring'''
_lowerCAmelCase : Optional[Any] = ... | 16 | 0 |
import json
import os
import re
import unittest
from transformers import CodeGenTokenizer, CodeGenTokenizerFast
from transformers.models.codegen.tokenization_codegen import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_common import TokenizerT... | 712 |
"""simple docstring"""
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert import BertTokenizer
_lowerCAmelCase =... | 16 | 0 |
"""simple docstring"""
import unittest
from transformers import DebertaVaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_com... | 713 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, skip_... | 16 | 0 |
"""simple docstring"""
import flax.linen as nn
import jax
import jax.numpy as jnp
class __UpperCamelCase ( nn.Module ):
_UpperCAmelCase = 42
_UpperCAmelCase = jnp.floataa
def __lowerCamelCase ( self ):
'''simple docstring'''
... | 714 |
"""simple docstring"""
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class __UpperCamelCase... | 16 | 0 |
"""simple docstring"""
import argparse
import random
import joblib
import numpy as np
import torch
from igf.igf import (
SecondaryLearner,
collect_objective_set,
compute_perplexity,
generate_datasets,
load_gpta,
recopy_gpta,
set_seed,
train_secondary_learner,
)
from torch.utils.... | 715 |
"""simple docstring"""
import argparse
import json
import os
from pathlib import Path
import requests
import torch
from transformers import JukeboxConfig, JukeboxModel
from transformers.utils import logging
logging.set_verbosity_info()
_lowerCAmelCase = logging.get_logger(__name_... | 16 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase = logging.get_logger(__name__)
_lowerCAmelCase = {
"""microsoft/trocr-base-handwritten""": (
"""https://huggingface.co/microsoft/trocr-base-handwrit... | 716 |
"""simple docstring"""
from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
_lowerCAmelCase = {"""UserAgent""": UserAgent().random}
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstr... | 16 | 0 |
"""simple docstring"""
from __future__ import annotations
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstring'''
if len(_lowerCamelCase ) == 0:
return array
_lowerCAmelCase : Optional[Any] = min(_lowerCamelCase ), max(_lowerCamelCa... | 717 |
"""simple docstring"""
import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import SPIECE_UNDERLINE, logging
_lowerCAmelCase... | 16 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase = logging.get_logger(__name__)
_lowerCAmelCase = {
"""caidas/swin2sr-classicalsr-x2-64""": (
"""https://huggingface.co/caidas/swin2sr-classicalsr-x2... | 718 |
"""simple docstring"""
import argparse
import struct
import unittest
class __UpperCamelCase :
def __init__( self ,_A ):
'''simple docstring'''
_lowerCAmelCase : Optional[int] = data
# Initialize hash values
_lowerCAmelCase ... | 16 | 0 |
"""simple docstring"""
import warnings
from transformers import AutoTokenizer
from transformers.utils import is_torch_available
from transformers.utils.generic import ExplicitEnum
from ...processing_utils import ProcessorMixin
if is_torch_available():
import torch
clas... | 719 |
"""simple docstring"""
from collections.abc import Callable
class __UpperCamelCase :
def __init__( self ,_A = None ):
'''simple docstring'''
_lowerCAmelCase : list = []
# Stores indexes of each item for supporting updates and deletion.... | 16 | 0 |
"""simple docstring"""
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : List[Any] = [1]
_lowerCAmelCase : List[str] = 0, 0, 0
_lowerCAmelCase : Union[str, Any] = ugly_nums[ia] * 2
_lowerCAm... | 720 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Dict, Optional, Union
import torch
import torch.nn.functional as F
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTra... | 16 | 0 |
"""simple docstring"""
import sys
from collections.abc import Mapping
from typing import TYPE_CHECKING, Dict, Optional
import numpy as np
import pyarrow as pa
from .. import config
from ..utils.logging import get_logger
from ..utils.py_utils import map_nested
from .formatting import TensorF... | 721 |
"""simple docstring"""
# Lint as: python3
import sys
from collections.abc import Mapping
from typing import TYPE_CHECKING, Dict, Optional
import numpy as np
import pyarrow as pa
from .. import config
from ..utils.logging import get_logger
from ..utils.py_utils import map_nested
from .forma... | 16 | 0 |
"""simple docstring"""
import os
from itertools import chain
from random import randrange, shuffle
import pytest
from .sola import PokerHand
_lowerCAmelCase = (
"""4S 3H 2C 7S 5H""",
"""9D 8H 2C 6S 7H""",
"""2D 6D 9D TH 7D""",
"""TC 8C 2S JH 6C""",
"""JH 8S TH ... | 700 |
"""simple docstring"""
from math import acos, sin
from typing import List, Tuple, Union
import numpy as np
import torch
from PIL import Image
from ...models import AutoencoderKL, UNetaDConditionModel
from ...schedulers import DDIMScheduler, DDPMScheduler
from ...utils import randn_tensor
fr... | 16 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_alig... | 701 |
"""simple docstring"""
import json
import os
from typing import Dict, List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_lowerCAmelCase = logging.get_logger(__name__)
_lowerCAmelCase = {
"""vocab_file""": """vocab.j... | 16 | 0 |
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert import BertTokenizer
_lowerCAmelCase = logging.get_logger(__name__)
_l... | 702 |
"""simple docstring"""
import math
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from .attention_processor import Attention
from .embeddings import get_timestep_embedding
from .modeling_utils import ModelMixin
class __Upper... | 16 | 0 |
"""simple docstring"""
import os
from pickle import UnpicklingError
from typing import Dict, Tuple
import jax
import jax.numpy as jnp
import numpy as np
from flax.serialization import from_bytes
from flax.traverse_util import flatten_dict, unflatten_dict
import transformers
from .utils i... | 703 |
"""simple docstring"""
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import ResNetConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_visio... | 16 | 0 |
from numpy import exp, pi, sqrt
def lowerCamelCase__ ( _lowerCamelCase , _lowerCamelCase = 0.0 , _lowerCamelCase = 1.0 ):
'''simple docstring'''
return 1 / sqrt(2 * pi * sigma**2 ) * exp(-((x - mu) ** 2) / (2 * sigma**2) )
if __name__ == "__main__":
import doctest
do... | 704 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Callable
_lowerCAmelCase = list[list[float | int]]
def lowerCamelCase__ ( _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : int = len... | 16 | 0 |
"""simple docstring"""
import os
from typing import List, Optional, Union
from ...image_processing_utils import BatchFeature
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextInput, ... | 705 |
"""simple docstring"""
import argparse
import json
from typing import List
from ltp import LTP
from transformers import BertTokenizer
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstring'''
if (
(cp >= 0X4E00 and cp <= 0X9FFF)
or (cp >= 0... | 16 | 0 |
"""simple docstring"""
import inspect
import logging
import os
import random
import shutil
import tempfile
import unittest
import pytest
import torch
from torch import nn
from torch.utils.data import DataLoader, TensorDataset
from accelerate import Accelerator
from accelerate.test_utils... | 706 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LDMTextToImagePipeline, UNetaDConditionModel
from diffusers.utils.testing_utils import (
... | 16 | 0 |
"""simple docstring"""
import json
import os
from typing import Dict, List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_lowerCAmelCase = logging.get_logger(__name__)
_lowerCAmelCase = {
"""vocab_file""": """vocab.j... | 707 |
"""simple docstring"""
import baseaa
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstring'''
return baseaa.aaaencode(string.encode('utf-8' ) )
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstring'''
return baseaa.aaadecod... | 16 | 0 |
"""simple docstring"""
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase = logging.get_logger(__name__)
_lowerCAmelCase = {
"""xlnet-base-cased""": """https://huggingface.co/xlnet-base-cased/resolve/main/config.... | 708 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bert import BertTokenizer
_lowerCAmelCase = logging.get_logge... | 16 | 0 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
_lowerCAmelCase = logging.get_logger(__name__)
... | 709 |
"""simple docstring"""
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_multi_gpu
from accelerate.utils import patch_environment
class __UpperCamelCas... | 16 | 0 |
import unittest
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare... | 710 |
"""simple docstring"""
from __future__ import annotations
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstring'''
create_state_space_tree(_lowerCamelCase , [] , 0 , [0 for i in range(len(_lowerCamelCase ) )] )
def lowerCamelCase__ ( _lowerCam... | 16 | 0 |
"""simple docstring"""
from __future__ import annotations
from scipy.special import comb # type: ignore
class __UpperCamelCase :
def __init__( self ,_A ):
'''simple docstring'''
_lowerCAmelCase : Dict = list_of_points
# Degree determines the flexibility of... | 711 |
"""simple docstring"""
import logging
import os
from .state import PartialState
class __UpperCamelCase ( logging.LoggerAdapter ):
@staticmethod
def __lowerCamelCase ( _A ):
'''simple docstring'''
_lowerCAmelCase : Optional[Any] = ... | 16 | 0 |
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
ConditionalDetrConfig,
ConditionalDetrForObjectDetection,
ConditionalDetrForSe... | 712 |
"""simple docstring"""
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert import BertTokenizer
_lowerCAmelCase =... | 16 | 0 |
"""simple docstring"""
import qiskit
def lowerCamelCase__ ( _lowerCamelCase = 2 ):
'''simple docstring'''
_lowerCAmelCase : List[str] = qubits
# Using Aer's simulator
_lowerCAmelCase : List[str] = qiskit.Aer.get_backend('aer_simulator' ... | 713 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, skip_... | 16 | 0 |
"""simple docstring"""
import argparse
import json
import math
import os
import time
import traceback
import zipfile
from collections import Counter
import requests
def lowerCamelCase__ ( _lowerCamelCase , _lowerCamelCase=None ):
'''simple docstring'''
_lowerCA... | 714 |
"""simple docstring"""
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class __UpperCamelCase... | 16 | 0 |
"""simple docstring"""
from __future__ import annotations
import math
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstring'''
if num <= 0:
_lowerCAmelCase : int = f"""{num}: Invalid input, please enter a positive integer."""
raise ValueError(_lowerCame... | 715 |
"""simple docstring"""
import argparse
import json
import os
from pathlib import Path
import requests
import torch
from transformers import JukeboxConfig, JukeboxModel
from transformers.utils import logging
logging.set_verbosity_info()
_lowerCAmelCase = logging.get_logger(__name_... | 16 | 0 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bert import BertTokenizer
_lowerCAmelCase = logging.get_logge... | 716 |
"""simple docstring"""
from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
_lowerCAmelCase = {"""UserAgent""": UserAgent().random}
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstr... | 16 | 0 |
"""simple docstring"""
from jiwer import compute_measures
import datasets
_lowerCAmelCase = """\
@inproceedings{inproceedings,
author = {Morris, Andrew and Maier, Viktoria and Green, Phil},
year = {2004},
month = {01},
pages = {},
title = {From WER and RIL to MER and W... | 717 |
"""simple docstring"""
import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import SPIECE_UNDERLINE, logging
_lowerCAmelCase... | 16 | 0 |
"""simple docstring"""
from math import sqrt
import numpy as np
from sympy import symbols
# Coefficient
# Speed of light (m/s)
_lowerCAmelCase = 2_9_9_7_9_2_4_5_8
# Symbols
_lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase = symbols("""ct x y z""")
... | 718 |
"""simple docstring"""
import argparse
import struct
import unittest
class __UpperCamelCase :
def __init__( self ,_A ):
'''simple docstring'''
_lowerCAmelCase : Optional[int] = data
# Initialize hash values
_lowerCAmelCase ... | 16 | 0 |
"""simple docstring"""
import argparse
from transformers import (
TapasConfig,
TapasForMaskedLM,
TapasForQuestionAnswering,
TapasForSequenceClassification,
TapasModel,
TapasTokenizer,
load_tf_weights_in_tapas,
)
from transformers.utils import logging
logging... | 719 |
"""simple docstring"""
from collections.abc import Callable
class __UpperCamelCase :
def __init__( self ,_A = None ):
'''simple docstring'''
_lowerCAmelCase : list = []
# Stores indexes of each item for supporting updates and deletion.... | 16 | 0 |
"""simple docstring"""
from datetime import datetime as dt
import os
from github import Github
_lowerCAmelCase = [
"""good first issue""",
"""good second issue""",
"""good difficult issue""",
"""feature request""",
"""new model""",
"""wip""",
]
def low... | 720 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Dict, Optional, Union
import torch
import torch.nn.functional as F
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTra... | 16 | 0 |
"""simple docstring"""
from collections import OrderedDict
from ...utils import logging
from .auto_factory import _BaseAutoModelClass, _LazyAutoMapping, auto_class_update
from .configuration_auto import CONFIG_MAPPING_NAMES
_lowerCAmelCase = logging.get_logger(__name__)
_lowerCAmel... | 721 |
"""simple docstring"""
# Lint as: python3
import sys
from collections.abc import Mapping
from typing import TYPE_CHECKING, Dict, Optional
import numpy as np
import pyarrow as pa
from .. import config
from ..utils.logging import get_logger
from ..utils.py_utils import map_nested
from .forma... | 16 | 0 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.utils import l... | 17 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__SCREAMING_SNAKE_CASE = {
"""configuration_instructblip""": [
"""INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""InstructBlipConfig""",
"""I... | 17 | 1 |
def UpperCAmelCase ( _lowerCamelCase ):
if not isinstance(_lowerCamelCase , _lowerCamelCase ):
raise TypeError("Input value must be an 'int' type" )
A : Tuple = 0
while number:
position += 1
number >>= 1
return position
... | 17 |
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_tf
if is_tf_available():
import tensorflow as tf
from tensorflow.python.eager import context
from tensorflow.python.framework import ops
from transformers import Gra... | 17 | 1 |
def UpperCAmelCase ( _lowerCamelCase , _lowerCamelCase = False ):
if not isinstance(_lowerCamelCase , _lowerCamelCase ):
A : List[str] = f"""Expected string as input, found {type(_lowerCamelCase )}"""
raise ValueError(_lowerCamelCase )
... | 17 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__SCREAMING_SNAKE_CASE = {
"""configuration_altclip""": [
"""ALTCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""AltCLIPConfig""",
... | 17 | 1 |
def UpperCAmelCase ( _lowerCamelCase ):
A : List[str] = len(_lowerCamelCase )
for i in range(length - 1 ):
A : Tuple = i
for k in range(i + 1 , _lowerCamelCase ):
if collection[k] < collection[least]:
... | 17 |
import importlib
import inspect
import json
import os
import re
import shutil
import sys
from pathlib import Path
from typing import Dict, Optional, Union
from urllib import request
from huggingface_hub import HfFolder, cached_download, hf_hub_download, model_info
from packaging import version
f... | 17 | 1 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version(""">=""", """4.25.0""")):
raise Optional... | 17 |
import math
import os
import re
import sys
import unittest
from pathlib import Path
from typing import Tuple
from unittest.mock import patch
from parameterized import parameterized
from transformers.testing_utils import (
CaptureStderr,
ExtendSysPath,
TestCasePlus,
execute_subpr... | 17 | 1 |
from diffusers.utils.testing_utils import require_onnxruntime
@require_onnxruntime
class lowerCamelCase_ :
'''simple docstring'''
pass | 17 |
from collections.abc import Sequence
def UpperCAmelCase ( _lowerCamelCase = None ):
if nums is None or not nums:
raise ValueError("Input sequence should not be empty" )
A : Dict = nums[0]
for i in range(1 , len(_lowerCamelCase ) ):... | 17 | 1 |
from __future__ import annotations
import pandas as pd
def UpperCAmelCase ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase ):
A : str = [0] * no_of_processes
A : Any = [0] * no_of_processes
# Copy the burst tim... | 17 |
from math import sqrt
def UpperCAmelCase ( _lowerCamelCase = 100_0000 ):
A : int = 0
A : int = 0
A : int
while num_cuboids <= limit:
max_cuboid_size += 1
for sum_shortest_sides in range(2 , 2... | 17 | 1 |
from __future__ import annotations
from typing import Any
class lowerCamelCase_ ( _A ):
'''simple docstring'''
pass
class lowerCamelCase_ :
'''simple docstring'''
def __init__( self : str , __lowerCamelCas... | 17 |
import os
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_doctest_list.py
__SCREAMING_SNAKE_CASE = """."""
if __name__ == "__main__":
__SCREAMING_SNAKE_CASE = os.path.join(REPO_PATH, """utils... | 17 | 1 |
def UpperCAmelCase ( _lowerCamelCase ):
if not isinstance(_lowerCamelCase , _lowerCamelCase ):
A : Dict = f"""Input value of [number={number}] must be an integer"""
raise TypeError(_lowerCamelCase )
if number < 1:
A : Tup... | 17 |
import inspect
import unittest
import warnings
from transformers import DeiTConfig
from transformers.models.auto import get_values
from transformers.testing_utils import (
require_accelerate,
require_torch,
require_torch_gpu,
require_vision,
slow,
torch_device,
)
from tran... | 17 | 1 |
from __future__ import annotations
def UpperCAmelCase ( _lowerCamelCase , _lowerCamelCase = None , _lowerCamelCase = None ):
if start is None:
A : Union[str, Any] = 0
if end is None:
A : Optional[int] = len... | 17 |
from sklearn.metrics import recall_score
import datasets
__SCREAMING_SNAKE_CASE = """
Recall is the fraction of the positive examples that were correctly labeled by the model as positive. It can be computed with the equation:
Recall = TP / (TP + FN)
Where TP is the true positives and FN is th... | 17 | 1 |
def UpperCAmelCase ( _lowerCamelCase , _lowerCamelCase ):
A : List[str] = len(_lowerCamelCase )
A : Optional[Any] = [[False] * (required_sum + 1) for _ in range(arr_len + 1 )]
# for each arr value, a sum of zero(0) can be ... | 17 |
from collections import deque
from .hash_table import HashTable
class lowerCamelCase_ ( _A ):
'''simple docstring'''
def __init__( self : Union[str, Any] , *__lowerCamelCase : Dict , **__lowerCamelCase : int ) -> Optional[int]:
... | 17 | 1 |
import argparse
import os
import re
import torch
from flax.traverse_util import flatten_dict
from tax import checkpoints
from transformers import (
AutoTokenizer,
PixaStructConfig,
PixaStructForConditionalGeneration,
PixaStructImageProcessor,
PixaStructProcessor,
PixaStru... | 17 |
import unittest
from typing import Tuple
import torch
from diffusers.utils import floats_tensor, randn_tensor, torch_all_close, torch_device
from diffusers.utils.testing_utils import require_torch
@require_torch
class lowerCamelCase_ :
'''simple docstring'''
... | 17 | 1 |
from binascii import hexlify
from hashlib import shaaaa
from os import urandom
# RFC 3526 - More Modular Exponential (MODP) Diffie-Hellman groups for
# Internet Key Exchange (IKE) https://tools.ietf.org/html/rfc3526
__SCREAMING_SNAKE_CASE = {
# 1536-bit
5: {
"""prime""": i... | 17 |
import time
import warnings
from abc import ABC
from copy import deepcopy
from typing import Optional
import torch
from ..utils import add_start_docstrings, logging
__SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE = r"""
Args:
inp... | 17 | 1 |
import numpy as np
class lowerCamelCase_ :
'''simple docstring'''
def __init__( self : Dict ) -> Optional[Any]:
A : str = (0, 0)
A : List[Any] = None
A : ... | 17 |
from sympy import diff, lambdify, symbols
from sympy.functions import * # noqa: F403
def UpperCAmelCase ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase = "x" , _lowerCamelCase = 10**-10 , _lowerCamelCase = 1 , ):
A : str = symbols(_lowerCam... | 17 | 1 |
import torch
from diffusers import DiffusionPipeline
class lowerCamelCase_ ( _A ):
'''simple docstring'''
def __init__( self : int , __lowerCamelCase : str , __lowerCamelCase : List[str] ) -> Tuple:
super().__init__()
... | 17 |
import json
from typing import Dict, List, Optional, Tuple, Union
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding, EncodedInput
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import PaddingStrategy, logging... | 17 | 1 |
import os
import shutil
import sys
import tempfile
import unittest
from pathlib import Path
import pytest
import transformers
from transformers import (
BERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP,
AutoTokenizer,
BertConfig,
BertTokenizer,
Ber... | 17 |
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Sequence, Value
from .base import TaskTemplate
@dataclass(frozen=_A )
class lowerCamelCase_ ( _A ):
'''simple docstring'''
# `task` is not a ClassVar since... | 17 | 1 |
import unittest
import numpy as np
from transformers import RobertaPreLayerNormConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_available()... | 17 |
import inspect
import unittest
from transformers import BitConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import BackboneTesterMixin
fro... | 17 | 1 |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requi... | 17 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
if is_torch_available():
import torch
from transformers import XLMRobertaModel
@require_sentencepiece
@require_tokenize... | 17 | 1 |
import json
import logging
import os
import socket
import git
import numpy as np
import torch
logging.basicConfig(
format="""%(asctime)s - %(levelname)s - %(name)s - PID: %(process)d - %(message)s""",
datefmt="""%m/%d/%Y %H:%M:%S""",
level=logging.INFO,
)
__SCREAMING_SNAKE_CASE ... | 17 |
from __future__ import annotations
import inspect
import unittest
from typing import List, Tuple
from transformers import RegNetConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ..... | 17 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__SCREAMING_SNAKE_CASE = {
"""configuration_instructblip""": [
"""INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""InstructBlipConfig""",
"""I... | 17 |
import tempfile
import torch
from diffusers import PNDMScheduler
from .test_schedulers import SchedulerCommonTest
class lowerCamelCase_ ( _A ):
'''simple docstring'''
a__ = (PNDMScheduler,)
a__ = (("num_inference_steps", 50),)
def ... | 17 | 1 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__SCREAMING_SNAKE_CASE = {
"""configuration_mctct""": ["""MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MCTCTConfig"""],
"""feature_extraction_mctct""": ["""MCTCTFeatu... | 17 |
from __future__ import annotations
from math import pi
# Define the Reduced Planck Constant ℏ (H bar), speed of light C, value of
# Pi and the function
__SCREAMING_SNAKE_CASE = 1.0_5_4_5_7_1_8_1_7e-3_4 # unit of ℏ : J * s
__SCREAMING_SNAKE_CASE = 3e8 # unit of c : m * s^-1
... | 17 | 1 |
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